
info.debatty.spark.knngraphs.example.Search Maven / Gradle / Ivy
/*
* The MIT License
*
* Copyright 2015 Thibault Debatty.
*
* Permission is hereby granted, free of charge, to any person obtaining a copy
* of this software and associated documentation files (the "Software"), to deal
* in the Software without restriction, including without limitation the rights
* to use, copy, modify, merge, publish, distribute, sublicense, and/or sell
* copies of the Software, and to permit persons to whom the Software is
* furnished to do so, subject to the following conditions:
*
* The above copyright notice and this permission notice shall be included in
* all copies or substantial portions of the Software.
*
* THE SOFTWARE IS PROVIDED "AS IS", WITHOUT WARRANTY OF ANY KIND, EXPRESS OR
* IMPLIED, INCLUDING BUT NOT LIMITED TO THE WARRANTIES OF MERCHANTABILITY,
* FITNESS FOR A PARTICULAR PURPOSE AND NONINFRINGEMENT. IN NO EVENT SHALL THE
* AUTHORS OR COPYRIGHT HOLDERS BE LIABLE FOR ANY CLAIM, DAMAGES OR OTHER
* LIABILITY, WHETHER IN AN ACTION OF CONTRACT, TORT OR OTHERWISE, ARISING FROM,
* OUT OF OR IN CONNECTION WITH THE SOFTWARE OR THE USE OR OTHER DEALINGS IN
* THE SOFTWARE.
*/
package info.debatty.spark.knngraphs.example;
import info.debatty.java.graphs.NeighborList;
import info.debatty.java.graphs.Node;
import info.debatty.java.graphs.SimilarityInterface;
import info.debatty.java.stringsimilarity.JaroWinkler;
import info.debatty.spark.knngraphs.ApproximateSearch;
import info.debatty.spark.knngraphs.ExhaustiveSearch;
import info.debatty.spark.knngraphs.builder.Brute;
import info.debatty.spark.knngraphs.builder.DistributedGraphBuilder;
import java.io.IOException;
import java.util.ArrayList;
import java.util.List;
import java.util.Random;
import org.apache.spark.SparkConf;
import org.apache.spark.api.java.JavaPairRDD;
import org.apache.spark.api.java.JavaRDD;
import org.apache.spark.api.java.JavaSparkContext;
/**
*
* @author Thibault Debatty
*/
public class Search {
/**
* @param args the command line arguments
* @throws java.io.IOException
*/
public static void main(String[] args) throws IOException, Exception {
if (args.length != 1) {
System.out.println(
"Usage: spark-submit --class " +
Search.class.getCanonicalName() + " " +
"");
}
String file = args[0];
// Graph building parameters
int k = 10;
// Partitioning parameters
int partitioning_iterations = 5;
int partitioning_medoids = 4;
// Search parameters
final int search_k = 10;
final int max_similarities = 400;
int search_queries = 10;
// Similarity measure
final SimilarityInterface similarity =
new SimilarityInterface() {
public double similarity(String value1, String value2) {
JaroWinkler jw = new JaroWinkler();
return jw.similarity(value1, value2);
}
};
// Read the dataset file
ArrayList strings = DistributedGraphBuilder.readFile(file);
// Configure spark instance
SparkConf conf = new SparkConf();
conf.setAppName("SparkTest");
conf.setIfMissing("spark.master", "local[*]");
JavaSparkContext sc = new JavaSparkContext(conf);
// Convert to nodes
List> dataset = new ArrayList>();
for (String s : strings) {
dataset.add(new Node(String.valueOf(dataset.size()), s));
}
// Split the dataset between training and validation
Random rand = new Random();
ArrayList> validation_dataset = new ArrayList>(search_queries);
for (int i = 0; i < search_queries; i++) {
validation_dataset.add(dataset.remove(rand.nextInt(dataset.size())));
}
// Parallelize the dataset and force execution
JavaRDD> nodes = sc.parallelize(dataset);
nodes.cache();
nodes.first();
// Compute the graph (and force execution)...
DistributedGraphBuilder builder = new Brute();
builder.setK(k);
builder.setSimilarity(similarity);
JavaPairRDD, NeighborList> graph = builder.computeGraph(nodes);
graph.cache();
graph.first();
// Prepare the graph for approximate graph based search
// (and force execution)
ApproximateSearch approximate_search_algorithm =
new ApproximateSearch(
graph,
partitioning_iterations,
partitioning_medoids,
similarity);
// Prepare exhaustive search
ExhaustiveSearch exhaustive_search =
new ExhaustiveSearch(graph, similarity);
graph.cache();
graph.first();
// Perform some search...
for (final Node query : validation_dataset) {
System.out.println("Search query: " + query.value);
// Using distributed graph based NN-search
NeighborList neighborlist_graph =
approximate_search_algorithm.search(
query,
search_k,
max_similarities);
System.out.println(
"Using graph: " + neighborlist_graph.element().node.value);
// Using distributed exhaustive search
NeighborList neighborlist_exhaustive =
exhaustive_search.search(query, search_k);
System.out.println(
"Using exhaustive search: " +
neighborlist_exhaustive.element().node.value);
}
}
}
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